Hepatitis

VideoRFSplat: Direct Scene-Level Text-to-3D Gaussian Splatting Generation with Flexible Pose and Multi-View Joint Modeling

We propose VideoRFSplat, a direct text-to-3D model leveraging a video generation model to generate realistic 3D Gaussian Splatting (3DGS) for unbounded real-world scenes. To generate diverse camera poses and unbounded spatial extent of real-world scenes, while ensuring generalization to arbitrary text prompts, previous methods fine-tune 2D generative models to jointly model camera poses and mult...

A deep learning model trained on expressed transcripts across different tissue types reveals cell-type codon-optimization preferences.

Species-specific differences in protein translation can affect the design of protein-based drugs. Consequently, efficient expression of recombinant proteins often requires codon optimization. Publicly available optimization tools do not always result in higher expression levels and can lead to protein misfolding and reduced expression. Here, we aimed to develop a novel deep learning (DL) tool usin...

COVID 19 Diagnosis Analysis using Transfer Learning

Coronaviruses, including SARS-CoV-2, are responsible for COVID-19, a highly transmissible disease that emerged in December 2019 in Wuhan, China. Dur...

VaxGuard: A Multi-Generator, Multi-Type, and Multi-Role Dataset for Detecting LLM-Generated Vaccine Misinformation

Recent advancements in Large Language Models (LLMs) have significantly improved text generation capabilities. However, they also present challenges,...

Treble Counterfactual VLMs: A Causal Approach to Hallucination

Vision-Language Models (VLMs) have advanced multi-modal tasks like image captioning, visual question answering, and reasoning. However, they often g...

Accelerated Patient-specific Non-Cartesian MRI Reconstruction using Implicit Neural Representations

The scanning time for a fully sampled MRI can be undesirably lengthy. Compressed sensing has been developed to minimize image artifacts in accelerat...

To Vaccinate or not to Vaccinate? Analyzing $\mathbb{X}$ Power over the Pandemic

The COVID-19 pandemic has profoundly affected the normal course of life -- from lock-downs and virtual meetings to the unprecedentedly swift creatio...

Application of Interpretable Machine Learning Models to Predict the Risk Factors of HBV-Related Liver Cirrhosis in CHB Patients Based on Routine Clinical Data: A Retrospective Cohort Study.

Chronic hepatitis B (CHB) infection represents a significant global public health issue, often leading to hepatitis B virus (HBV)-related liver cirrho...

Enhancing Hepatopathy Clinical Trial Efficiency: A Secure, Large Language Model-Powered Pre-Screening Pipeline

Background: Recruitment for cohorts involving complex liver diseases, such as hepatocellular carcinoma and liver cirrhosis, often requires interpret...

Liver Cirrhosis Stage Estimation from MRI with Deep Learning

We present an end-to-end deep learning framework for automated liver cirrhosis stage estimation from multi-sequence MRI. Cirrhosis is the severe sca...

Re-Align: Aligning Vision Language Models via Retrieval-Augmented Direct Preference Optimization

The emergence of large Vision Language Models (VLMs) has broadened the scope and capabilities of single-modal Large Language Models (LLMs) by integr...

Machine learning algorithm approach to complete blood count can be used as early predictor of COVID-19 outcome.

Although the SARS-CoV-2 infection has established risk groups, identifying biomarkers for disease outcomes is still crucial to stratify patient risk a...

Cancer Vaccine Adjuvant Name Recognition from Biomedical Literature using Large Language Models

Motivation: An adjuvant is a chemical incorporated into vaccines that enhances their efficacy by improving the immune response. Identifying adjuvant...

Fast Direct: Query-Efficient Online Black-box Guidance for Diffusion-model Target Generation

Guided diffusion-model generation is a promising direction for customizing the generation process of a pre-trained diffusion model to address specif...

Development and Validation of a Novel Model to Discriminate Idiosyncratic Drug-Induced Liver Injury and Autoimmune Hepatitis.

BACKGROUND AND AIM: Discriminating between idiosyncratic drug-induced liver injury (DILI) and autoimmune hepatitis (AIH) is critical yet challenging. ...

Identification and Validation of Biomarkers in Metabolic Dysfunction-Associated Steatohepatitis Using Machine Learning and Bioinformatics.

BACKGROUND: The incidence of metabolic dysfunction-associated steatohepatitis (MASH) is increasing annually. MASH can progress to cirrhosis and hepato...

CHiP: Cross-modal Hierarchical Direct Preference Optimization for Multimodal LLMs

Multimodal Large Language Models (MLLMs) still struggle with hallucinations despite their impressive capabilities. Recent studies have attempted to ...

A CNN-Transformer for Classification of Longitudinal 3D MRI Images -- A Case Study on Hepatocellular Carcinoma Prediction

Longitudinal MRI analysis is crucial for predicting disease outcomes, particularly in chronic conditions like hepatocellular carcinoma (HCC), where ...

DPERC: Direct Parameter Estimation for Mixed Data

The covariance matrix is a foundation in numerous statistical and machine-learning applications such as Principle Component Analysis, Correlation He...

VirusImmu: a novel ensemble machine learning approach for viral immunogenicity prediction.

The viruses threats provoke concerns regarding their sustained epidemic transmission, making the development of vaccines particularly important. In th...